DQ Global http://www.dqglobal.com Making Data Fit for Business Wed, 20 May 2015 16:01:46 +0000 en-US hourly 1 http://wordpress.org/?v=4.2.2 Were the Election Polls Marred by Poor Quality Data? http://www.dqglobal.com/were-the-election-polls-marred-by-poor-quality-data/ http://www.dqglobal.com/were-the-election-polls-marred-by-poor-quality-data/#comments Tue, 12 May 2015 13:37:32 +0000 http://www.dqglobal.com/?p=19052 Were the Election Polls Marred by Poor Quality Data?

Were-the-Election-Polls-Marred-by-Poor-Quality-DataThe UK’s general election took place last week, on Thursday 7 May, 2015. It was an election that had been hyped for being ‘too close to call’. According to the polls, the government was likely to be a coalition of one or more, with no party achieving a majority. It could have gone either way.


Imagine the shock when the BBC announced the exit poll results: a landslide victory for a single party – the Conservatives.

Election polling companies are reliant on various types of data to come up with accurate predictions. Like any business, they must apply quality control to their data. They must cleanse it, eradicate errors and duplicates, and ensure their contact records are up to date. They need to ensure they don’t call the same person twice, and they must encourage people to give accurate data in response.

How could so many companies get it so badly wrong? And was the data at fault, or was there another gremlin in the machine?

Precedents in polls

This is not the first time that polling data has let down the public, politicians and press.

During the US election in 2012, opinion polls predicted a tough campaign for President Obama. He wound up with a comfortable majority. And in 1992, there was a direct comparison with last week’s data disaster. A close race was predicted; the Conservatives won comfortably then, too.

Even this year, in March, polling companies in Israel underestimated support for Netanyahu’s Likud party. He was, in the end, a clear winner.

Even though polls are not binding, they influence voters in the run up to an election, and can even influence the policies that parties formulate as they seek to capture the mood of the electorate. It’s therefore critical that polls can be relied upon. And that makes it a matter of data quality.

How data is sourced

Election polling companies get their data from a variety of sources. YouGov has posted an excellent blog detailing how its surveys work.

In brief, YouGov (and similar organisations) collect data by determining preference for a particular party. Responses are gathered online, and over the phone.

Initially, it’s tempting to think that perhaps different voters have different ways of answering polls. But YouGov adjusts for this already. Labour voters are more likely to use online methods, and Conservative voters the telephone. But it says the data being collected was the same via each method. So we can rule out ‘mode effects’ based on this.

Another culprit is a change in turnout. The polling companies take a small data sample and extrapolate the results, based on the size of the actual sample. So they could be filling in blanks in the wrong way.

Dissecting data collection

YouGov says that there may be “methodological failure” in the way these polls are being conducted.

Interviewers may be asking questions in a loaded way, or influencing the answers by their mere presence.

In the US, polling companies are legally required to manually dial mobile telephone numbers. They do not have to manually dial landlines. This has lead to the landline being favoured, and it’s possible that – culturally – this habit has been persistent in the UK, too. Due to automated calls and marketing campaigns – both relatively new phenomena – some of us view landline telephone calls with suspicion. We want to get off the phone as quickly as possible, so perhaps the data we give is hurried, or we say what we think we should say to get it over with.

They may have asked the wrong questions: how people would vote on local issues, for example, rather than which leader or party was favourable at a national level.

But there may be a more mundane reason. When collecting data, you have to assume that the data is being provided truthfully and accurately. If someone gives you their email address, you need to trust that it will be genuine.

It may be that some people did not supply accurate data to the polling company in the first place: they “said one thing and did another”. This is what Peter Kellner, president of YouGov, thinks is most likely to be the problem. Marketers face this problem all the time: people provide fake information in order to avoid being added to marketing lists. Could it be that people are just less inclined to tell the truth?

The consequences of poor quality data

As providers of data quality software, we have a saying. “Junk in – junk out.”

Whether it’s a company balance sheet, a marketing report or an election poll, the outputs that are generated are only ever going to be as good as the data that was used to build them. This is why data quality is so critical to success and profitability.

Think of it in simple terms. If you compile a list of 1,000 contacts and send a marketing letter to all of them, you need a clean list: one free of mistakes, duplicates, misspellings and ‘gone away’ records.

If you get 500 letters ‘returned to sender’, you can safely assume that your mailing list is seriously decayed. Not only is that inconvenient, but it’s effectively doubled the cost of your campaign: 50% of the effort was wasted.

For polling companies, their entire business model is based on obtaining accurate data, and purifying data to ensure they have a reliable snapshot. They need to take small, frequent samples via polling to gain an understanding of wider trends. This means mistakes are going to be amplified, as they clearly were last week. Now, more than ever, data accuracy is the number one goal.

If telephone polling is less reliable, companies now face a new era, where response rates and accuracy need to be higher. The British Polling Council is conducting an enquiry into the reasons behind last week’s failure. Data quality will undoubtedly be placed under the spotlight. Without it, we may never fully trust election polls again.

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Do Your Customers Hide Their Data? http://www.dqglobal.com/do-your-customers-hide-their-data/ http://www.dqglobal.com/do-your-customers-hide-their-data/#comments Tue, 28 Apr 2015 08:19:59 +0000 http://www.dqglobal.com/?p=19035 Do Your Customers Hide Their Data?


Personal data has an image problem. People are increasingly wary of handing over their details to websites – particularly when they have no intention to engage long term. Many marketers set out to obtain email addresses, yet do very little to ensure the email addresses they get are valid. This is the beginning of a vicious circle for the business they’re working for.

Why? Trust has broken down. If customers don’t trust you, they will hide their data from view.

Official advice from tech-savvy gurus is to hide your real personal data from the prying eyes of advertisers, by entering false dates and other booby traps. In 2012, this advice was even given by the UK government as a way to protect security and stay safe online.

This is a dirty data nightmare for small businesses, and it will only serve to compound the considerable problems we already face with bad data.

Where We Are Now

According to the Telegraph newspaper, half of British consumers think their data is at risk. They cite data loss, theft and surveillance – all key issues that have hit the news. Paranoia? Not necessarily. Consumers are not merely influenced by media reporting. They have first hand experience of data abuse:

  • 59 per cent said they have experienced a data protection issue
  • 53 per cent of people avoid posting personal data online
  • 33 per cent type in fake data


The figures quoted are from Symantec’s 2015 State of Privacy report – a reliable industry source.

How Did We Get Here?

In some respects, less ethical marketers only have themselves to blame. They have pushed the boundaries of personal data collection, harvesting information for marketing purposes when the customer was unaware, and using phone numbers and addresses to sign people up to mailing lists they never wanted to join.

One key reason for this is the sheer number of agreements we sign up to online. In truth, none of us has time to pore over every single privacy policy, or pick over the contents of every Terms and Conditions pop-up that we’re asked to review. Sometimes, we skip over the detail. We place trust in companies that perhaps do not deserve it. And our data is left wide open for abuse.

In fact, according to the same Symantec report, 80 per cent of surveyed users do not read terms and conditions. These may well describe how data is stored and used, but we’d never even know.

Social networking sites have come in for their fair share of controversy too, thanks to some liberties taken with advertising tracking – the Facebook Beacon being one of the first. High-profile hacks at companies like Sony and LinkedIn also serve to make people nervous.

What Happens Now?

This worry about personal data hasn’t stopped people from using the internet or engaging with businesses on some level. They have simply adapted their behaviour to protect themselves.

Over time, Symantec believes that customers will vote with their feet. They will find businesses that manage data properly; businesses they deem to be safe. Customers will then develop new spending habits, and simply migrate their custom on that basis.

Not only is bad data costing you money, but it could force customers to your competitors.

What Do We Do Next?

The key take-away is that people are still handing over data to businesses. But the balance of trust has shifted

Because of hacking, or unethical marketing, or poor management of data, consumers have started to mask personal information.

In the future, we will see two different changes. On the one hand, businesses will have more data to sift through and organise, and there will be bigger penalties for its misuse, compounding the cost of poor data management. On the other, customers will start to consider price, quality and data management when making a buying decision.

In order to be profitable going forward, a business will not be able to be the best or cheapest. There has to be a third factor: responsibility to manage data properly.

This means:

  • Transparency in the way data is managed – no hidden terms and long agreements to read
  • Quality of data, so that customers know they will be contacted at appropriate points in the relationship
  • Accuracy of data, so that customers know their data is being cared for, not corrupted and left to decay

Data quality is a barrier to efficiency and accuracy. If you are harvesting email addresses in return for an incentive, and those email addresses are being deliberately obfuscated because trust has broken down, this can cause a ripple effect in terms of wasted effort, wasted materials and a dreadful ROI.

This is not a theoretical problem. It’s something that third party resources already face. Integrate analysed more than 775,000 leads generated for marketers working in the B2B sector, and they found that 40 per cent did not meet the client’s requirements in terms of quality or accuracy.

If your customers are deliberately making it difficult to obtain good quality leads, this kind of data quality shortfall is only going to become more expensive.

Finding a Way Forward

In some ways, it’s positive that consumers care about data. And it’s interesting that they recognise its value as an asset. (Many businesses would benefit from realising this, too.)

More than half believe their personal data is worth more than €1,000.

Indeed, when it’s accurate, and well-managed, personal data could be worth ten times more. It all depends on what the business does with it, and how effectively it’s used in automation, segmentation and reporting. And it depends on how well it’s cared for, or whether it’s left to go stale and wither away.

But without validation, and that critical element of trust, the data in a business’ CRM system may as well be the data from a five year old telephone directory. It simply won’t serve its purpose, and it could have negative consequences for customers and profits alike.

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Enhance your CRM Data to Sharpen your Sales Pitch http://www.dqglobal.com/enhance-your-crm-data-to-sharpen-your-sales-pitch/ http://www.dqglobal.com/enhance-your-crm-data-to-sharpen-your-sales-pitch/#comments Wed, 08 Apr 2015 10:46:56 +0000 http://www.dqglobal.com/?p=18693 Enhance your CRM Data to Sharpen your Sales Pitch

Enhance-your-CRM-Data-to-Sharpen-your-Sales-Pitch twitter

In the old days, you knew who to contact to make business. There were a few job functions, and a few levels of seniority. A name with job function was usually enough for you to hit the bullseye more often than not. But as businesses diversify and become more complex, this becomes more difficult; and even for the “data-aware”, old habits die hard.

I had an interesting conversation this week with a potential business partner I was trying to reach out to. This was an organisation that I had done a bit of old school research on, understood their target market and modus operandi as best I could from their website and LinkedIn, and decided that it was definitely worth investigating further. So with my “sales research” head on, I made the call to their London office with a name & job role in my hand that I thought would give me more information and might be able to progress the idea of a partnership. When researching, I always start with people who can give me the most information and confirm / correct my assumptions, rather than diving in cold.

So I speak with John, tell him what I do and where I think there may be a great fit with his company. John goes silent for a moment, and then puts his hand across the receiver and says to his colleague “this chap wants XYZ, what’s the name of the fella that deals with this? He’s in Europe right?”

After a bit more muffled deliberation, John gives me the name and number of the man who thinks he can help me, though he’s not sure of his exact role but it’s “definitely more his area than mine”

Here’s my Sliding Doors moment….

In this reality, I put a call straight through to my newly identified contact. The vagueness of the information made me think “I’ll call this guy, he’s probably not the absolute contact, but I’m definitely one step closer”. We have a great conversation over 20 minutes once he gets the general idea of my proposition. He’s a lovely guy, and it turns out that what I’m proposing is possibly something that would be of mutual benefit to our companies. I send him an outline of how we work and we promise to speak again in a week, although I may have to bear with him as he is travelling a lot and has a fair few other priorities. As we are closing the call I tell him I’m just dropping on to LinkedIn to connect with him. And that’s when I discover that he is the CEO of this business.

In my alternate reality, I go to LinkedIn 1st to search specifically for this name. I discover that “that fella in Europe” is the CEO. This is all well and good, but I then decide to get more of a hook. I search for him in our online business universe (which I can use to populate CRM automatically). On a single page I discover his email address, as well as 7 web references related to him that lay out his history and future vision for the business in blogs, interviews and articles. Armed with this information, I sharpen my pitch substantially, and make my call.

Data is the lifeblood of the modern economy, but the arrangement of that data into information and knowledge is what really helps to make those better, more memorable connections. Research is key. The important point here is that, for the busy sales professional, that information is available in neatly packaged bundles. Somebody else has done it for you, so that you can make more calls and enter validated, more accurate, more complete contact information into your CRM. No longer do you need to spend vital time trawling the internet, if you have the condensed information at your fingertips. And for the data-shy salesperson, you don’t even have to re-key the information anymore. You still have to click the “update CRM” button with your hand however, but I’m sure someone somewhere is working on that.

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How a Chief Data Officer Can Make Your Data Great http://www.dqglobal.com/how-a-chief-data-officer-can-make-your-data-great/ http://www.dqglobal.com/how-a-chief-data-officer-can-make-your-data-great/#comments Wed, 25 Mar 2015 10:48:18 +0000 http://www.dqglobal.com/?p=18452 How a Chief Data Officer
Can Make Your Data Great

How-a-Chief-Data-Officer-Can-make-Your-Data-Great-twitterFresh data is usually pristine. It’s data in it’s clearest, most accurate form – straight from the customer or client. If you’ve put measures in place to cut back on data input errors, such as form validation, you can be reasonably sure that the newest records in your CRM are the “latest and greatest”.

If your CRM has been active for some time, you’ll have a number of older records that have accrued. These records are the ones your sales and marketing teams will rely on when it’s time to approach existing customers and sell to them again. Chances are, the quality of these records will be fairly good, but it will have fallen since they were first collected. As data quality slips, data goes from “great”, to “good”, to decidedly “bad”.

Waste and Cost

Data management is a huge cost to businesses, but it’s the bad data that is the real drain. According to Gartner, the average business wastes as much as $13.5 million sorting out data quality problems every year.

Poor management is rife. Because data is stored electronically, many businesses leave its management to the IT department. Yet there is no role within IT that is adept at managing data, and no role that traditionally takes ownership of it. People expect data to retain its accuracy when stored, yet the exact opposite is true. Data ages, decays and loses all of its value.

Enter the Chief Data Officer.

One job role cannot be a panacea for poor data management. And in itself, the role isn’t a data quality cure-all. But the Chief Data Officer can take ownership of a potential pain point, and they can make sure that the business’ most valuable asset is not allowed to depreciate over time.

What a CDO Can Do

The role of Chief Data Officer is relatively new, yet it’s a role that is well overdue in tens of thousands of businesses. We’re all harvesting more data about our customers, and that calls for investment in people who can nurture and manage that data. The Chief Data Officer is tasked with making order from chaos, and with protecting the investment with the digital contents of some of the most important storage silos the company has.

Take the customer relationship management system, for example. As CRMs begin to age, the data within them is the tell-tale sign of trouble ahead. Once ‘great’ data is now simply ‘good’ data. If left unchecked, this data will turn ‘bad’ pretty quickly.

Once in post, the Chief Data Officer can migrate data management responsibilities to the business as a whole, taking it away from IT (or marketing, or whichever function is currently responsible for it). This puts data quality at the core of the business’ operations, making it a central point of discussion when new business processes are developed. It should also result in data quality receiving adequate resources.

The Chief Data Officer can also keep track of data assets: where they’re stored, who’s got access, and how often they are cleansed and checked. They can put data quality processes in place to better manage the purity of critical business data, and they can make sure the business is not paying to store duplicated, old, unverified or corrupted data.

The end result is a cleaner, clearer dataset for everyone in the business, and a more secure, timely and effective management of data for the customer or client.

What a CDO Can’t Do

It sounds as though the Chief Data Officer will wave their magic wand and solve the business’ data quality problems. But let’s be clear: one person cannot be solely responsible for managing data in any business.

There must be a broader strategic aim to treat data as an asset, care for it while it’s at rest, and use it responsibly when it’s needed. This is something the Chief Data Officer can oversee, but with support and buy-in from the boardroom.

This isn’t a solo mission, and this is why the Chief Data Officer is expected to take a senior role in the company, according to Gartner’s paper.

From medical records to loyalty cards, there are myriad rules around how personal data can be used and stored. It’s the Chief Data Officer’s responsibility to oversee this. Yet other staff using the data will still be expected to understand compliance, and must handle data responsibly according to those regulations.

Moving Forward With Data

Businesses are capturing more and more data from an increasing range of sources. Customer data, such as names and addresses, represent the core of most CRM systems. As we become better at capturing data, we’re certainly going to acquire more of it, more quickly than ever before.

From the Internet of Things to increasingly sophisticated web analytics, businesses are going to need to be more selective about data, and store only the data that really matters to them. This increasing resource will need ongoing management to ensure it does not go from ‘great’, to ‘good’, to ‘bad’ – or even ‘useless’.

And as our data silos grow, they become more appealing to hackers who will try their best to gain access by stealth. Often, by a time a breach has been discovered, the data has been sold on multiple times, and the business is powerless to do anything about it.

This is the unfortunate end result of data being badly managed, or not managed at all.

By 2017, Gartner says that 25 per cent of organisations will have a Chief Data Officer. In industries where regulatory compliance is key, the figure is expected to be much higher; perhaps even 50 per cent. If your business collects data, stores it and uses it to determine strategy, a Chief Data Officer could be the key person who will commit to high data quality across the business.

Watch our up coming webinar on 15.04.15 on “How to Make the Leap from Good to Great Data”

The webinar will take place twice, choose your suitable time:

2:00-2:30 GMT Click to register 

2:00-2:30 EDT-5 Click to register 

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Data Quality – Supporting Your Sales Team’s Unnatural Disposition http://www.dqglobal.com/data-quality-supporting-your-sales-teams-unnatural-disposition/ http://www.dqglobal.com/data-quality-supporting-your-sales-teams-unnatural-disposition/#comments Wed, 18 Mar 2015 11:07:04 +0000 http://www.dqglobal.com/?p=18272 Data Quality – Supporting Your Sales Team’s Unnatural Disposition


I should start by saying that I love data – or more importantly I love the information that data can unveil to an enquiring mind. I am seldom happier than when I am looking for trends in whether salespeople decide to make more telephone calls straight after the sales meeting on Tuesday afternoons, what the average sales cycle is for Widget A versus Thingummy X, and if there is a correlation between customer spend and activity. I could spend hours in there, figuratively speaking.

However, I’m afraid I am a walking cliché – a sales professional with a natural disposition to spend as much time as possible talking to clients, and as little time as possible in the “non-revenue-generating” task of capturing the correct and complete data in my CRM system. Salespeople don’t do attention to detail, right? They are the hunter-gatherers who stalk the beast, slay the beast, bring the beast back home and put it on the fire they made. Someone else can do the washing up. If they did attention to detail, they’d work in systems analysis surely?

Well yes, all of this is true. Up to a point. I called it a natural disposition deliberately. It doesn’t mean I don’t do quality data capture, it just means that I need to work at it a little harder. I do this because my many years of working in sales have lead me to witness the odd uncomfortable situation, such as;

  • Products, desperately needed, sat at the wrong office because I didn’t check the address properly
  • Commissions on substantial orders left unpaid, as the invoice sent from the washing up department known as Accounts disappeared into the black hole that I’d created. Compounded by the cost of replacing the bit of worn-out carpet between my desk and the financial controller’s office
  • Losing a whole day to trawl through my CRM before I could answer the simple request from Marketing, “who would you like to target with this campaign?”
  • Bare-knuckle brawling on the sales floor over 2 John Smith’s at ABC Co, on whom 2 of us had been working simultaneously on separate CRM records (I exaggerate, slightly, and some names have been changed to protect the innocent)

All of the above semi-fictional scenarios lead to loss, or waste. Loss of reputation, time, and revenues. That’s why now I work a little harder. I may not always get it right, but my heart’s in the right place.

So from the lofty position of Sales Director I can impart this well-earned wisdom to sales teams. I can reward commissions based on completeness of the data. I can even use psychometrics to ensure that I recruit salespeople who have a high natural disposition to attention to detail and completeness, also often known as an Introvert Thinking style. However if I have a “sales rock star” in my team who is consistently overachieving and is loved by clients, but CRM-averse, then perhaps the easy thing for me to do is to accept the odd bit of wasted profit and inter-departmental ill feeling?

Luckily there is another way. I’m now fortunate enough to work for an organisation that is passionate about data being the lifeblood of business. And what I’ve discovered is that companies who whole-heartedly embrace this principle do so not through a top-down, push behaviour approach. Rather, they create a culture that encourages everyone to contribute to absolute data quality, and support them with the tools, techniques and technology to do so.

Technology to enhance, validate, verify, authenticate and cleanse your customer data is readily available. It comes from DQ Global. And the good news is, it costs much, much less than the cost of lost orders, duplicate mailings, missed opportunities and replacement carpet.

If as a Sales and/or Marketing Director, you have just made a career-defining investment in a CRM system, it is worth considering what you are also doing to protect that investment; to protect the lifeblood of your organisation. If those brilliant yet data-shy salespeople in your team are finding it too difficult to overcome their natural disposition, and are risking the value of the data you hold inside that expensive new vehicle, then perhaps we could talk.



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Value your Customer Data as a Business Asset http://www.dqglobal.com/value-your-customer-data-as-a-business-asset/ http://www.dqglobal.com/value-your-customer-data-as-a-business-asset/#comments Wed, 04 Mar 2015 14:16:34 +0000 http://www.dqglobal.com/?p=18237 Value your Customer Data as a Business Asset


Private data is now a very public issue. For the first time in history, people recognise that businesses store their information and they want to know how – and why. They want to know why websites need their email address so badly, and they understand that private photos can be hacked.

Privacy and security are legitimate concerns for everyone who hands over information about themselves. But some businesses don’t share that opinion. Or, if the business understands the value of data, it has yet to do anything about protecting it.

Your business may have all kinds of excuses for this. Your CEO may think that data management is too expensive, or that workflows are too ingrained to be changed. You might think your business is too small to be hacked, or too big to be affected by a breach.

But no matter how many excuses you have, your customers are getting smarter. They know the value of data, and they want to trust you to understand it too.

Data Risks

Data silos contain all kinds of data; some that could identify a person, and some that cannot. The diversity of these data sets is staggering. Names, addresses and telephone numbers are fairly standard, but as our use of mobile devices evolves, millions of other records are being stored alongside contact records.

A company like Google or Facebook also holds our location information, the details of our closest friends, and an algorithm that can pick out our facial features. The wearable devices we carry around are counting the steps we take and snapping photos of the world around us.

At the same time, our digital environment is constantly generating and saving data. The equipment we use at home, and at work, is generating reams of data about itself and its users. The Internet of Things is the next logical stage in our digital evolution, where the machines around us can constantly report their status back to their peers. And all of this data has value.

Data, whether big or small, presents huge opportunities for businesses and marketers. Yet there is a weak link in the chain: poor data management.

data silos

Evasive Action

Data needs to be held securely, and quality must be maintained to prevent error, misuse and waste. But according to a Telegraph report, half of British consumers believe that their personal data could be compromised and used for malicious purposes.

Media attention has placed a spotlight on data and highlights just how dependent businesses are on it. Far from being an asset, or an abstract, it is now a personal matter. 59 per cent of users surveyed said that they had experienced a problem relating to data protection; a huge number, when we strive so hard to comply with the law.

The Telegraph report highlights the consequences of letting data quality slip. It demonstrates how savvy customers feel about their data and the businesses that hold and use it. Many have simply lost their trust, and they are taking their privacy into their own hands by deliberately forcing the data to be inaccurate. One-third of those surveyed said that they had introduced fake information into their own records to protect their privacy. (53 per cent simply avoid giving any accurate data at all.)

Data owners are effectively scrambling their personal details, just in case the worst happens and another party misuses a database. These customers are protecting themselves against faulty data management and irresponsible businesses, because they know there are businesses out there that don’t take their data seriously enough.

Will your business be the one they can actually trust?

The Cost of Lost Confidence

If out of date data could be considered wasteful, then data that has been intentionally obfuscated is positively useless.

If your customers are typing in inaccurate ages, hiding their locations or deliberately misspelling their address, there is absolutely no way that their data can be used for accurate reporting or profitable outcomes. In many cases, no amount of data cleansing can correct those intentional errors; they are simply a wasted opportunity for the business.

The survey we’ve mentioned also highlighted the fact that users recognise the value of their own data, even if the business does not. Some valued their information at more than €10,000, while many understood that a single record was worth more than €1,000. From loyalty campaigns to market segmentation, businesses must also know just how critical accurate data is to their future profitability.

Finally, consider this: respondents valued data integrity as highly as the quality of the business’ products and services. That proves that data management, quality and security are already part of the buying decision for many users. Data management and data quality are effectively an extra dimension to brand reputation, and we will all pay more attention to this over the coming months and years.

Building Trust

If your business does not yet have a data quality plan in place, it’s not too late to begin the journey.

Your chief data officer should be tasked with aligning business objectives with the effective management of data; that means making sure your customers must have confidence in what you’re doing.

Marketing teams need access to quality data – not deliberately mangled records, or incomplete personal profiles. And the IT department should be storing clean, deduplicated data in a secure fashion, rather than being forced to archive messy, dirty databases full of records that should have been purged.

By caring about their data, your customers are asking you to care, too. They are asking you to place a value on data as an asset, and they are demanding that their own personal data is protected. If you focus on caring for their data, your brand reputation will be protected, and your customers are more likely to stay loyal to your business as it grows.

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Do You Have a Love-Hate Relationship With Your Data? http://www.dqglobal.com/do-you-have-a-love-hate-relationship-with-your-data/ http://www.dqglobal.com/do-you-have-a-love-hate-relationship-with-your-data/#comments Tue, 17 Feb 2015 11:08:59 +0000 http://www.dqglobal.com/?p=18195 Do You Have a Love-Hate Relationship With Your Data?


Can’t live with it? Can’t live without it?

Has your relationship with data seen better days?

When the business is ticking over nicely, and data is fresh, everyone’s content and happy. They can get on with their work, free from the burden of decrepit databases and phone numbers that never connect.

But then the honeymoon period ends, and the relationship needs work. It’s getting harder to email people. You’re always getting names wrong. And half of your mail comes back as returned to sender.

Like Elvis’ love letter, your mail need not be sent back with an ‘address unknown’. Just as Valentine’s Day gave us all good excuse to nurture relationships and ensure their longevity, it gives us the opportunity to reflect on the way we relate to data, and whether we spend enough time on making sure it’s working for us.

Invest in the Best

Last weekend, the world spent around $13 billion on Valentine’s Day. We shopped for 180 million cards, bought 196 million roses and spent $2.2 billion on jewellery.

Over a year, businesses spend a fraction of that amount on data quality initiatives – a ‘mere’ $994 million in 2012, according to The Information Difference.

So we clearly spend far more nurturing our partners than we do nurturing the best asset our business could ever acquire. In context, it’s clear that both require investment if they are to survive. While Hallmark Cards have a healthy future ahead, we need to spend more on our much-loved and much-valued data, and invest more time in measuring genuine return on investment.

Love Data… in the Real World

Dating site OKCupid uses sophisticated data matching in order to pair up potential lovebirds. Its algorithms are responsible for sorting through more than 70 terabytes of data about the people in its database. Their likes, dislikes, personality quirks and ideal matches all paint a unique portrait of what they’re looking for in life – and in love.

Naturally, people change. OKCupid has to continue to keep people engaged in enriching their own data and updating it frequently – or until the right match comes along. In essence, it’s an exercise in big data management. And just as errors are introduced unwittingly into big data, so dating sites have to cope with people’s idiosyncrasies. They have to filter out the noise and use data to define the person you really are.

If you’re in any doubt about the value of accurate data, look at OKCupid. It’s data is worth millions. The company was purchased four years ago for $50 million, primarily because it uses data to gain unbeatable insight into its users, and it understands how to purify and segment its data to ensure the matches it achieves are second to none.

When is Dirty Data Good Enough?

Some opponents will argue that data is “good enough” in its current state. They will argue that data quality is too much of an expense, and unless your business is also worth $50 million, there are few gains to be had by correcting it. These colleagues have certainly fallen out of love with data; they are so used to developing workarounds that they will argue the case against change.

Granted, there are some – very limited – scenarios where data need not be timely and precise. For example, when we touch on big data, we immediately think about data sets filled with noise, junk, error and anomaly. It would be foolish to presume that all big data could be cleaned and honed precisely, since big data generation never stands still for a second.

Many of us are so used to tolerating imperfect data that we daren’t imagine a world where data is clean and accurate. We fell out of love with our data, and learned to live with its growing flaws. We accepted the fact that our data would tell us a white lie now and then. But remember the simple saying: “garbage in, garbage out”. Eventually, bad data will come back to haunt you – a skeleton in the closet that never quite disappears.

Rescuing the Relationship

Remember the golden rule of customer retention? It’s much cheaper to sell to an existing client, rather than trying to market to a new one.

But hear this. If your data is ageing, inaccurate and unreliable, take that saying with a large pinch of salt.

Most businesses understand that investments in data quality will pay dividends. They fail to appreciate the rising cost of inaction. Measuring this is difficult, but Econsultancy spells out the potential consequences and pitfalls very nicely in its 2014 poll:

  • Poor data from the website means no action can be taken to follow up
  • Poor face to face data capture injects errors into a live database
  • Lack of error correction lets bad data linger unchecked
  • Bad data renders loyalty programs useless
  • Mis-addressed mail results in waste
  • Manual checks are completely inefficient in dealing with data problems

If your data isn’t loved and cared for, it will eventually wither away. But you and data are not done yet. You can rescue your ailing relationship by giving your data some attention now. And improving the way you acquire new data will help you avoid hiccups as your data matures.

A little tender loving care will future-proof existing data and help you build insights and knowledge that will fuel the business and drive growth for years to come.

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Using Customer Data? Start With Clean Data http://www.dqglobal.com/using-customer-data-start-with-clean-data/ http://www.dqglobal.com/using-customer-data-start-with-clean-data/#comments Tue, 27 Jan 2015 16:17:45 +0000 http://www.dqglobal.com/?p=18078

Using Customer Data? Start With Clean Data


Office, the high street shoe retailer, has had something of a lucky escape when it comes to its data quality. Last week, the Information Commissioner’s Office decided not to levy a fine on the company for a massive data leak, although luck had its part to play in the outcome

In May 2014, hackers gained access to Office’s servers and stole customer information relating to more than a million past customers. Sensitive data, such as postal addresses, was exposed, and the hackers were also able to steal passwords from the database. Fortunately, none of this data appears to have been used for malicious purposes.

For many businesses, the consequences of a hack are severe. Fines, bad publicity and compensation payments can have serious consequences for profitability. This is why master data management is a key concept in information security, and achieving a state of security and consistency is critical.

Lucky Escapes

The reason the Office hack was so serious was because the database was so large, and so old. It contained out of data, ‘dirty’ contact information – records that should have been deleted when a new database was brought online. Instead of quickly merging the old database with the new one, Office held back and chose to sit on the old data as it decayed and sat neglected on a server nobody remembered was there.

The old database was taking up space, for one thing, and costing money by the by, but that’s not the worst of Office’s worries. It was stored in a location nobody monitored, and it was fast becoming a liability for the business without it even realising.

Unfortunately, when the hackers got in to the old database, there was plenty to steal. The data had not been deduplicated, matched and merged with new records. What’s more, the old database was unencrypted, and that was the final flaw that exposed this vast dataset to prying eyes.

According to Gartner, businesses have become accomplished at simply coping with bad data, rather than doing something about it. Rather than tackling the data quality challenges of merging data and perfecting it, Office chose to simply hide the data, which meant that customer details were held without proper checks and governance.

Dealing with Old Data

All businesses are faced with upgrades and data migration at some stage in their evolution, and the need for merging of datasets becomes greater as the business matures. Legacy systems get phased out and replaced, and employees ditch old ways of working when better solutions are brought online. Often, compliance guidelines force a change in the way data is stored and managed, and new team members can bring new systems and fresh ideas.

In Office’s case, staff felt that migrating the old data was risky. One of its key concerns was an inability to match the old data to the new data. As such, there was a problem with duplicates from day one. But managing data properly means that the business needs to understand how data is being used. If that means dropping old databases completely, that’s what has to be done.

Yes, businesses are right to approach data migration with caution. Invalid entries are a huge source of data quality problems, and merging two datasets can be a source of huge data corruption. This can result in confusion for staff; fields that should contain fixed values may contain all kinds of invalid results, and this can even stop records from saving when they fail automatic validation checks.

Customer Control

Businesses that retain personal data have to work within the law, which compounds the risk that poor data quality presents. The holder of data must make sure that it is accurate, and held for a reasonable period of time. These requirements are not new, yet businesses are still failing to address the risk that poor data quality presents, and failing to spot the obvious danger signs early on.

It’s easy to see why the Information Commissioner objected to the legacy system Office was using. It was uncontrolled, unmonitored and completely lacking updates. It could also be argued that customer data was held for far longer than it should have been, given that a newer system had already been brought online.

Lessons in Data Management

The Information Commissioners Office describes data as “vulnerable”. Using the same analogy, dirty data is data at its most exposed. This isn’t a case of increasing security (although an unencrypted database is clearly going to be vulnerable). It’s not simply a case of the IT department stepping up their controls.

In Article 5 of the Information Commissioner’s standards principles, there’s a clear requirement for data to be deleted as soon as it’s no longer needed. Clearly, the Office data breach proves why this is so important, and there needs to be a clear process and policy in place. Old data should be disposed of, new data cleansed at the point of entry, and ageing data regularly checked and managed using automated data quality solutions.

Managing data is also far easier if you don’t hold records you don’t need. If you delete records that you know are out of date, there are fewer risks to the business when you try to merge them. If you remove known duplicates using data quality software, there are fewer risks of customers being inconvenienced with wasteful duplicate communications.

Planning for Success

Data quality initiatives require strategic planning and concerted effort, and that means treating old data exactly the same as new. Just as new entries are filtered using form fields and validation, old data should be subjected to the same standards and checks.

A customer data warehouse is a key business asset, and it’s an asset your customers expect you to value and protect. Data governance requires the right people, the right funding and sustained effort, but the reward is an error-free dataset that does not expose any party to unnecessary risk.

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What is CRM – A Holistic Approach to Customer Relationship Mangement http://www.dqglobal.com/what-is-crm-a-holistic-approach-to-customer-relationship-mangement/ http://www.dqglobal.com/what-is-crm-a-holistic-approach-to-customer-relationship-mangement/#comments Wed, 21 Jan 2015 14:57:07 +0000 http://www.dqglobal.com/?p=18060 What is CRM – A Holistic Approach to Customer Relationship Management

A Holistic Approach to Customer Relationship ManagementIn a recent blog article by Salesforce, they explain what a CRM system is and the impact of using a CRM system can have on businesses. “CRM helps organizations be more effective and efficient in their day-to-day tasks and assists them in reaching long-term business objectives and goals”.

They go on to explain how technology for CRM systems has improved over the last couple of decades, allowing businesses to have access to powerful, comprehensive and affordable CRM systems.

The purpose of the CRM systems is to facilitate more efficient communication with customers and leads, helping all participants complete transactions quickly. Even the most technically advanced CRM cannot achieve its goals if the data it holds is inaccurate.

As we are all becoming aware, the data held in CRM systems is becoming one of the “Largest Assets” for businesses. Unless this data is maintained and treasured, businesses are at danger of their CRM systems failing and even the most technically advanced CRM cannot achieve its goals if the data it holds is inaccurate.

As we explained in one of our recent blog articles – If you are collecting data without any thought of data quality, your CRM could be a ticking time bomb.

Data quality is one of the biggest and most relevant risks to your CRM, and the longer you ignore it, the worse it will get – Read our blog Is the Data in Your CRM a Ticking Time Bomb?

Check out this Salesforce Infographic which highlights – A Holistic Approach to Customer Relationship Management.

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Is the Data in Your CRM a Ticking Time Bomb? http://www.dqglobal.com/is-the-data-in-your-crm-a-ticking-time-bomb/ http://www.dqglobal.com/is-the-data-in-your-crm-a-ticking-time-bomb/#comments Tue, 13 Jan 2015 16:08:23 +0000 http://www.dqglobal.com/?p=17982

Is the Data in Your CRM a Ticking Time Bomb?


Customer relationship management (CRM) has moved from specialist term to buzzword, and now, into the core of business. According to a blog by Sugar CRM, about 15 million people used some kind of CRM system in 2012. The same blog says that large businesses were more likely to adopt CRM software first, since the potential benefits are so much greater.

Gartner is well known for its predictions, and its analysis of the market is clear: the appeal of the CRM is growing, and smaller businesses are able to adopt the technology thanks to affordable pricing and cloud hosting. Gartner predicts that CRM software will grow at a rate of 14.8% through to 2017. That’s a lot of data being collected – and a huge potential for expense.

Harvest Time

The maturing CRM market is a reflection of our desire for data. Data lets us understand our customers, communicate more effectively with those customers, and segment them for more effective marketing. This is why many businesses harvest massive amounts of data about their customers and store it in their CRM, then leave it to fester, either neglecting it or harvesting even more.

Over time, simply collecting this data gives you your first potential for a ticking time bomb. The CRM becomes clogged up and weighed down by old and inaccurate contact records. This wastes money when it’s time to do mailshots, but it also wastes your employees’ time as they struggle to figure out which records are too old to be trusted.

Fancy Fields

As the CRM has become a standard feature in business, employees are expected to collect a broader set of data. Social media metrics are brought in, and soon there’s an embarrassment of riches: data about every interaction with every customer, or every lead that’s come into contact with your team. Each record could have hundreds of potential fields.

Maintaining all of these different records is a challenge for users, since manual entry becomes incredibly cumbersome when you add more potential entries. It’s human nature to try to take short cuts, so there’s a perfect storm brewing: a combination of highly specialised fields and a workforce who simply don’t have the time to populate them as you’d like them to.

There are two possible outcomes from this. One, you wind up with missing and incomplete data – a customer service disaster waiting to happen. Two, you could accumulate a large amount of data that is completed without due care and attention, making it poor quality right from the word go.

Sure, you could hire an administrator to manually fight the flow of bad data, but a continual flow of poor quality data coming in, combined with natural decay, means the return on investment will be next to nil.

Protection and Security

Most CRM software is designed for security, but there are always a few cracks in the armour. An unmanaged CRM is a possible source of a leak, and poor data handling can expose holes in your processes and workflows – flaws that could cost you dearly.

The Information Commissioner’s Office has the power to levy fines up to £500,000 for the poor handling of personal data, and there’s talk of these being increased to 5 per cent of global turnover. Information security is not optional, and anyone collecting customer data is vulnerable to prosecution, prison and brand disaster. One of the key provisions of this law is giving people control, allowing them to update and remove data at will. Could your CRM support this kind of granular maintenance? And is it in any fit state for you to try?

Decayed and dirty data in CRM systems and contact databases is costing businesses tens of thousands of pounds ever year, through penalties, brand damage and more. Poor record keeping, poor security and a failure to comply with consumer requests is a risk your business would be crazy to ignore. See the 8 Data protection principles by the ICO.

Staff Morale

Valuing staff is essential to limit churn and raise morale, and giving them the correct tools for the job is part of that. If you don’t solve your employees’ problems, you’re fighting a losing battle, and you will eventually lose them

Failing to acknowledge data decay, or take action to reverse the tide, is a sure fire way to store up problems for the future. As your CRM data becomes less useful, employees will waste their time trying to come up with workarounds. The CRM will become the system legendary for its poor data quality, and new staff will be warned off it from day one.

If you want your CRM to be used, and if you want it to support your employees, don’t expect them to work around its problems.

Saving the CRM

CRM data goes out of date every day. In the last 48 hours, someone in your database probably changed their email address, sold their house, got a new mobile number, moved offices, got a promotion or got married. It is an inevitability of data collection.

If you are collecting data without any thought of data quality, your CRM could be a ticking time bomb. Data cannot be trusted, enhanced or relied upon if it is becoming irrelevant and out-dated. Adding more data could just be increasing the likelihood of an explosion. Paying lip service to data quality with manual edits simply places your staff on an unfair trajectory towards failure.

Think of a CRM like a database. It contains records that are unusually time-sensitive: addresses, names, people’s personal details. Not only does this data decay incredibly quickly, but poor management could land you in hot water if you fail to meet compliance obligations. Data quality is therefore one of the biggest and most relevant risks to your CRM, and the longer you ignore it, the worse it will get.

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